Carga y limpieza preliminar de los datos
Los datos que se van a analizar en este documento proceden de la
compilación hecha por usuarios de Kaggle.
La fecha del análisis empieza el 22 de agosto de 2022, utilizando la
versión 166 recopilada en la web anterior.
Cargar el dataset correctamente
Carga del dataset desde Python
import pandas as pd
datos = pd.read_csv("data/covid_19_clean_complete.csv")
datos.head(10)
## Province/State ... WHO Region
## 0 NaN ... Eastern Mediterranean
## 1 NaN ... Europe
## 2 NaN ... Africa
## 3 NaN ... Europe
## 4 NaN ... Africa
## 5 NaN ... Americas
## 6 NaN ... Americas
## 7 NaN ... Europe
## 8 Australian Capital Territory ... Western Pacific
## 9 New South Wales ... Western Pacific
##
## [10 rows x 10 columns]
Carga del dataset con la librería reticulate
pd <- import("pandas")
datos <- pd$read_csv("data/covid_19_clean_complete.csv")
kable(head(datos, 10))
| NaN |
Afghanistan |
33.93911 |
67.70995 |
2020-01-22 |
0 |
0 |
0 |
0 |
Eastern Mediterranean |
| NaN |
Albania |
41.15330 |
20.16830 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
| NaN |
Algeria |
28.03390 |
1.65960 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
| NaN |
Andorra |
42.50630 |
1.52180 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
| NaN |
Angola |
-11.20270 |
17.87390 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
| NaN |
Antigua and Barbuda |
17.06080 |
-61.79640 |
2020-01-22 |
0 |
0 |
0 |
0 |
Americas |
| NaN |
Argentina |
-38.41610 |
-63.61670 |
2020-01-22 |
0 |
0 |
0 |
0 |
Americas |
| NaN |
Armenia |
40.06910 |
45.03820 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
| Australian Capital Territory |
Australia |
-35.47350 |
149.01240 |
2020-01-22 |
0 |
0 |
0 |
0 |
Western Pacific |
| New South Wales |
Australia |
-33.86880 |
151.20930 |
2020-01-22 |
0 |
0 |
0 |
0 |
Western Pacific |
Carga del dataset desde R
datos <- read.csv("data/covid_19_clean_complete.csv", stringsAsFactors = T)
datos %>% head(10) %>% kable()
|
Afghanistan |
33.93911 |
67.70995 |
2020-01-22 |
0 |
0 |
0 |
0 |
Eastern Mediterranean |
|
Albania |
41.15330 |
20.16830 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
|
Algeria |
28.03390 |
1.65960 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
|
Andorra |
42.50630 |
1.52180 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
|
Angola |
-11.20270 |
17.87390 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
|
Antigua and Barbuda |
17.06080 |
-61.79640 |
2020-01-22 |
0 |
0 |
0 |
0 |
Americas |
|
Argentina |
-38.41610 |
-63.61670 |
2020-01-22 |
0 |
0 |
0 |
0 |
Americas |
|
Armenia |
40.06910 |
45.03820 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
| Australian Capital Territory |
Australia |
-35.47350 |
149.01240 |
2020-01-22 |
0 |
0 |
0 |
0 |
Western Pacific |
| New South Wales |
Australia |
-33.86880 |
151.20930 |
2020-01-22 |
0 |
0 |
0 |
0 |
Western Pacific |
Estructura de los datos y cambio nombre de las columnas
str(datos)
## 'data.frame': 49068 obs. of 10 variables:
## $ Province.State: Factor w/ 79 levels "","Alberta","Anguilla",..: 1 1 1 1 1 1 1 1 6 47 ...
## $ Country.Region: Factor w/ 187 levels "Afghanistan",..: 1 2 3 4 5 6 7 8 9 9 ...
## $ Lat : num 33.9 41.2 28 42.5 -11.2 ...
## $ Long : num 67.71 20.17 1.66 1.52 17.87 ...
## $ Date : Factor w/ 188 levels "2020-01-22","2020-01-23",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ Confirmed : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Deaths : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Recovered : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Active : int 0 0 0 0 0 0 0 0 0 0 ...
## $ WHO.Region : Factor w/ 6 levels "Africa","Americas",..: 3 4 1 4 1 2 2 4 6 6 ...
colnames(datos) = c("Provincia_Estado",
"Pais_Region",
"Latitud", # N+ o S-
"Longitud", # E+ o W-
"Fecha",
"Casos_Confirmados",
"Casos_Muertos",
"Casos_Recuperados",
"Casos Activos",
"WHO_Region"
)
datos %>% head() %>% kable() # %>% kable_styling()
|
Afghanistan |
33.93911 |
67.70995 |
2020-01-22 |
0 |
0 |
0 |
0 |
Eastern Mediterranean |
|
Albania |
41.15330 |
20.16830 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
|
Algeria |
28.03390 |
1.65960 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
|
Andorra |
42.50630 |
1.52180 |
2020-01-22 |
0 |
0 |
0 |
0 |
Europe |
|
Angola |
-11.20270 |
17.87390 |
2020-01-22 |
0 |
0 |
0 |
0 |
Africa |
|
Antigua and Barbuda |
17.06080 |
-61.79640 |
2020-01-22 |
0 |
0 |
0 |
0 |
Americas |
Tipo de datos de cada columna
- Cualitativas se convierten
factor o bien
as.factor.
- Ordinales se convierten con
ordered.
- Cuantitativas se convierten con
as.numeric.
El tipo de dato fecha y su manipulación
Cambiar la columna fecha a tipo Date:
#datos$Fecha %<>% as.Date(format="%Y-%m-%d")
datos$Fecha %<>% ymd() # Con librería lubridate
str(datos)
## 'data.frame': 49068 obs. of 10 variables:
## $ Provincia_Estado : Factor w/ 79 levels "","Alberta","Anguilla",..: 1 1 1 1 1 1 1 1 6 47 ...
## $ Pais_Region : Factor w/ 187 levels "Afghanistan",..: 1 2 3 4 5 6 7 8 9 9 ...
## $ Latitud : num 33.9 41.2 28 42.5 -11.2 ...
## $ Longitud : num 67.71 20.17 1.66 1.52 17.87 ...
## $ Fecha : Date, format: "2020-01-22" "2020-01-22" ...
## $ Casos_Confirmados: int 0 0 0 0 0 0 0 0 0 0 ...
## $ Casos_Muertos : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Casos_Recuperados: int 0 0 0 0 0 0 0 0 0 0 ...
## $ Casos Activos : int 0 0 0 0 0 0 0 0 0 0 ...
## $ WHO_Region : Factor w/ 6 levels "Africa","Americas",..: 3 4 1 4 1 2 2 4 6 6 ...
\[Casos\ Confirmados = Muertos +
Recuperados + Enfermos\]
# Lo siguiente da lo mismo que la columna Casos_Activos, pero en el dataset que se
# utilizó en el curso no aparecía
datos %<>% # Ventaja que nos ofrece la librería magrittr
mutate(Casos_Enfermos = Casos_Confirmados - Casos_Muertos - Casos_Recuperados)
datos %>%
filter(Casos_Confirmados > 10000) %>%
head() %>%
kable()
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-02 |
11177 |
350 |
295 |
10532 |
Western Pacific |
10532 |
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-03 |
13522 |
414 |
386 |
12722 |
Western Pacific |
12722 |
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-04 |
16678 |
479 |
522 |
15677 |
Western Pacific |
15677 |
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-05 |
19665 |
549 |
633 |
18483 |
Western Pacific |
18483 |
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-06 |
22112 |
618 |
817 |
20677 |
Western Pacific |
20677 |
| Hubei |
China |
30.9756 |
112.2707 |
2020-02-07 |
24953 |
699 |
1115 |
23139 |
Western Pacific |
23139 |
datos %>%
filter(Casos_Enfermos < 0) %>%
arrange(Provincia_Estado, Fecha) %>%
kable()
|
Liechtenstein |
47.140000 |
9.55000 |
2020-06-23 |
82 |
2 |
81 |
-1 |
Europe |
-1 |
|
Uganda |
1.373333 |
32.29028 |
2020-07-20 |
1069 |
0 |
1071 |
-2 |
Africa |
-2 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-05-23 |
558 |
45 |
515 |
-2 |
Europe |
-2 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-05-24 |
558 |
45 |
517 |
-4 |
Europe |
-4 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-05-25 |
559 |
45 |
517 |
-3 |
Europe |
-3 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-05-30 |
560 |
45 |
525 |
-10 |
Europe |
-10 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-05-31 |
560 |
45 |
528 |
-13 |
Europe |
-13 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-06-01 |
560 |
45 |
528 |
-13 |
Europe |
-13 |
| Channel Islands |
United Kingdom |
49.372300 |
-2.36440 |
2020-06-02 |
560 |
46 |
528 |
-14 |
Europe |
-14 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-24 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-25 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-26 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-27 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-28 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-29 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-30 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-03-31 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.195900 |
109.74530 |
2020-04-01 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
datos %>%
filter(Provincia_Estado == "Hainan") %>%
kable()
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-22 |
4 |
0 |
0 |
4 |
Western Pacific |
4 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-23 |
5 |
0 |
0 |
5 |
Western Pacific |
5 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-24 |
8 |
0 |
0 |
8 |
Western Pacific |
8 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-25 |
19 |
0 |
0 |
19 |
Western Pacific |
19 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-26 |
22 |
0 |
0 |
22 |
Western Pacific |
22 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-27 |
33 |
1 |
0 |
32 |
Western Pacific |
32 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-28 |
40 |
1 |
0 |
39 |
Western Pacific |
39 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-29 |
43 |
1 |
0 |
42 |
Western Pacific |
42 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-30 |
46 |
1 |
1 |
44 |
Western Pacific |
44 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-01-31 |
52 |
1 |
1 |
50 |
Western Pacific |
50 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-01 |
62 |
1 |
1 |
60 |
Western Pacific |
60 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-02 |
64 |
1 |
4 |
59 |
Western Pacific |
59 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-03 |
72 |
1 |
4 |
67 |
Western Pacific |
67 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-04 |
80 |
1 |
5 |
74 |
Western Pacific |
74 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-05 |
99 |
1 |
5 |
93 |
Western Pacific |
93 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-06 |
106 |
1 |
8 |
97 |
Western Pacific |
97 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-07 |
117 |
2 |
10 |
105 |
Western Pacific |
105 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-08 |
124 |
2 |
14 |
108 |
Western Pacific |
108 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-09 |
131 |
3 |
19 |
109 |
Western Pacific |
109 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-10 |
138 |
3 |
19 |
116 |
Western Pacific |
116 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-11 |
144 |
3 |
20 |
121 |
Western Pacific |
121 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-12 |
157 |
4 |
27 |
126 |
Western Pacific |
126 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-13 |
157 |
4 |
30 |
123 |
Western Pacific |
123 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-14 |
159 |
4 |
43 |
112 |
Western Pacific |
112 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-15 |
162 |
4 |
39 |
119 |
Western Pacific |
119 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-16 |
162 |
4 |
52 |
106 |
Western Pacific |
106 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-17 |
163 |
4 |
59 |
100 |
Western Pacific |
100 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-18 |
163 |
4 |
79 |
80 |
Western Pacific |
80 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-19 |
168 |
4 |
84 |
80 |
Western Pacific |
80 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-20 |
168 |
4 |
86 |
78 |
Western Pacific |
78 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-21 |
168 |
4 |
95 |
69 |
Western Pacific |
69 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-22 |
168 |
4 |
104 |
60 |
Western Pacific |
60 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-23 |
168 |
5 |
106 |
57 |
Western Pacific |
57 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-24 |
168 |
5 |
116 |
47 |
Western Pacific |
47 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-25 |
168 |
5 |
124 |
39 |
Western Pacific |
39 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-26 |
168 |
5 |
129 |
34 |
Western Pacific |
34 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-27 |
168 |
5 |
131 |
32 |
Western Pacific |
32 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-28 |
168 |
5 |
133 |
30 |
Western Pacific |
30 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-02-29 |
168 |
5 |
148 |
15 |
Western Pacific |
15 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-01 |
168 |
5 |
149 |
14 |
Western Pacific |
14 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-02 |
168 |
5 |
151 |
12 |
Western Pacific |
12 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-03 |
168 |
5 |
155 |
8 |
Western Pacific |
8 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-04 |
168 |
5 |
158 |
5 |
Western Pacific |
5 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-05 |
168 |
6 |
158 |
4 |
Western Pacific |
4 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-06 |
168 |
6 |
158 |
4 |
Western Pacific |
4 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-07 |
168 |
6 |
158 |
4 |
Western Pacific |
4 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-08 |
168 |
6 |
159 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-09 |
168 |
6 |
159 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-10 |
168 |
6 |
159 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-11 |
168 |
6 |
159 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-12 |
168 |
6 |
160 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-13 |
168 |
6 |
160 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-14 |
168 |
6 |
160 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-15 |
168 |
6 |
160 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-16 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-17 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-18 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-19 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-20 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-21 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-22 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-23 |
168 |
6 |
161 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-24 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-25 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-26 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-27 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-28 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-29 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-30 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-31 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-01 |
168 |
6 |
168 |
-6 |
Western Pacific |
-6 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-02 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-03 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-04 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-05 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-06 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-07 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-08 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-09 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-10 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-11 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-12 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-13 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-14 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-15 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-16 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-17 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-18 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-19 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-20 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-21 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-22 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-23 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-24 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-25 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-26 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-27 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-28 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-29 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-30 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-01 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-02 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-03 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-04 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-05 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-06 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-07 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-08 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-09 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-10 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-11 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-12 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-13 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-14 |
168 |
6 |
162 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-15 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-16 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-17 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-18 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-19 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-20 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-21 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-22 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-23 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-24 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-25 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-26 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-27 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-28 |
169 |
6 |
162 |
1 |
Western Pacific |
1 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-29 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-30 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-05-31 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-01 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-02 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-03 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-04 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-05 |
169 |
6 |
163 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-06 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-07 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-08 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-09 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-10 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-11 |
170 |
6 |
162 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-12 |
171 |
6 |
162 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-13 |
171 |
6 |
162 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-14 |
171 |
6 |
162 |
3 |
Western Pacific |
3 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-15 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-16 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-17 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-18 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-19 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-20 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-21 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-22 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-23 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-24 |
171 |
6 |
163 |
2 |
Western Pacific |
2 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-25 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-26 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-27 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-28 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-29 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-06-30 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-01 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-02 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-03 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-04 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-05 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-06 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-07 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-08 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-09 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-10 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-11 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-12 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-13 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-14 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-15 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-16 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-17 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-18 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-19 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-20 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-21 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-22 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-23 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-24 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-25 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-26 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-07-27 |
171 |
6 |
165 |
0 |
Western Pacific |
0 |
Datos anómalos y sin sentido
# Corregir datos anómalos y sin sentido
datos %>%
filter(Provincia_Estado == "Hainan", Casos_Enfermos < 0) %>%
mutate(Casos_Recuperados = Casos_Recuperados + Casos_Enfermos,
Casos_Enfermos = 0) %>%
kable()
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-24 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-25 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-26 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-27 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-28 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-29 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-30 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-03-31 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
| Hainan |
China |
19.1959 |
109.7453 |
2020-04-01 |
168 |
6 |
162 |
-6 |
Western Pacific |
0 |
Análisis geográfico de los datos
#datos_europa = datos[datos$Latitud > 38 & datos$Longitud > -25 & datos$Longitud < 30 , ]
datos_europa = datos %>%
filter(Latitud > 38, between(Longitud, -25, 30))
nrow(datos_europa)
## [1] 8460
table(datos_europa$Pais_Region) %>%
as.data.frame() %>%
filter(Freq > 0) %>%
kable()
| Albania |
188 |
| Andorra |
188 |
| Austria |
188 |
| Belarus |
188 |
| Belgium |
188 |
| Bosnia and Herzegovina |
188 |
| Bulgaria |
188 |
| Croatia |
188 |
| Czechia |
188 |
| Denmark |
376 |
| Estonia |
188 |
| Finland |
188 |
| France |
188 |
| Germany |
188 |
| Greece |
188 |
| Holy See |
188 |
| Hungary |
188 |
| Iceland |
188 |
| Ireland |
188 |
| Italy |
188 |
| Kosovo |
188 |
| Latvia |
188 |
| Liechtenstein |
188 |
| Lithuania |
188 |
| Luxembourg |
188 |
| Moldova |
188 |
| Monaco |
188 |
| Montenegro |
188 |
| Netherlands |
188 |
| North Macedonia |
188 |
| Norway |
188 |
| Poland |
188 |
| Portugal |
188 |
| Romania |
188 |
| San Marino |
188 |
| Serbia |
188 |
| Slovakia |
188 |
| Slovenia |
188 |
| Spain |
188 |
| Sweden |
188 |
| Switzerland |
188 |
| United Kingdom |
564 |
datos_europa %>%
filter(Fecha == ymd("2020-03-15")) %>%
kable()
|
Albania |
41.15330 |
20.168300 |
2020-03-15 |
42 |
1 |
0 |
41 |
Europe |
41 |
|
Andorra |
42.50630 |
1.521800 |
2020-03-15 |
1 |
0 |
1 |
0 |
Europe |
0 |
|
Austria |
47.51620 |
14.550100 |
2020-03-15 |
860 |
1 |
6 |
853 |
Europe |
853 |
|
Belarus |
53.70980 |
27.953400 |
2020-03-15 |
27 |
0 |
3 |
24 |
Europe |
24 |
|
Belgium |
50.83330 |
4.469936 |
2020-03-15 |
886 |
4 |
1 |
881 |
Europe |
881 |
|
Bosnia and Herzegovina |
43.91590 |
17.679100 |
2020-03-15 |
24 |
0 |
0 |
24 |
Europe |
24 |
|
Bulgaria |
42.73390 |
25.485800 |
2020-03-15 |
51 |
2 |
0 |
49 |
Europe |
49 |
|
Croatia |
45.10000 |
15.200000 |
2020-03-15 |
49 |
0 |
1 |
48 |
Europe |
48 |
|
Czechia |
49.81750 |
15.473000 |
2020-03-15 |
253 |
0 |
0 |
253 |
Europe |
253 |
| Faroe Islands |
Denmark |
61.89260 |
-6.911800 |
2020-03-15 |
11 |
0 |
0 |
11 |
Europe |
11 |
|
Denmark |
56.26390 |
9.501800 |
2020-03-15 |
864 |
2 |
1 |
861 |
Europe |
861 |
|
Estonia |
58.59530 |
25.013600 |
2020-03-15 |
171 |
0 |
1 |
170 |
Europe |
170 |
|
Finland |
61.92411 |
25.748151 |
2020-03-15 |
244 |
0 |
10 |
234 |
Europe |
234 |
|
France |
46.22760 |
2.213700 |
2020-03-15 |
4499 |
91 |
12 |
4396 |
Europe |
4396 |
|
Germany |
51.16569 |
10.451526 |
2020-03-15 |
5795 |
11 |
46 |
5738 |
Europe |
5738 |
|
Greece |
39.07420 |
21.824300 |
2020-03-15 |
331 |
4 |
8 |
319 |
Europe |
319 |
|
Holy See |
41.90290 |
12.453400 |
2020-03-15 |
1 |
0 |
0 |
1 |
Europe |
1 |
|
Hungary |
47.16250 |
19.503300 |
2020-03-15 |
32 |
1 |
1 |
30 |
Europe |
30 |
|
Iceland |
64.96310 |
-19.020800 |
2020-03-15 |
171 |
5 |
8 |
158 |
Europe |
158 |
|
Ireland |
53.14240 |
-7.692100 |
2020-03-15 |
129 |
2 |
0 |
127 |
Europe |
127 |
|
Italy |
41.87194 |
12.567380 |
2020-03-15 |
24747 |
1809 |
2335 |
20603 |
Europe |
20603 |
|
Latvia |
56.87960 |
24.603200 |
2020-03-15 |
30 |
0 |
1 |
29 |
Europe |
29 |
|
Liechtenstein |
47.14000 |
9.550000 |
2020-03-15 |
4 |
0 |
1 |
3 |
Europe |
3 |
|
Lithuania |
55.16940 |
23.881300 |
2020-03-15 |
12 |
0 |
1 |
11 |
Europe |
11 |
|
Luxembourg |
49.81530 |
6.129600 |
2020-03-15 |
59 |
1 |
0 |
58 |
Europe |
58 |
|
Moldova |
47.41160 |
28.369900 |
2020-03-15 |
23 |
0 |
0 |
23 |
Europe |
23 |
|
Monaco |
43.73330 |
7.416700 |
2020-03-15 |
2 |
0 |
0 |
2 |
Europe |
2 |
|
Montenegro |
42.70868 |
19.374390 |
2020-03-15 |
0 |
0 |
0 |
0 |
Europe |
0 |
|
Netherlands |
52.13260 |
5.291300 |
2020-03-15 |
1135 |
20 |
0 |
1115 |
Europe |
1115 |
|
North Macedonia |
41.60860 |
21.745300 |
2020-03-15 |
14 |
0 |
1 |
13 |
Europe |
13 |
|
Norway |
60.47200 |
8.468900 |
2020-03-15 |
1221 |
3 |
1 |
1217 |
Europe |
1217 |
|
Poland |
51.91940 |
19.145100 |
2020-03-15 |
119 |
3 |
0 |
116 |
Europe |
116 |
|
Portugal |
39.39990 |
-8.224500 |
2020-03-15 |
245 |
0 |
2 |
243 |
Europe |
243 |
|
Romania |
45.94320 |
24.966800 |
2020-03-15 |
131 |
0 |
9 |
122 |
Europe |
122 |
|
San Marino |
43.94240 |
12.457800 |
2020-03-15 |
101 |
5 |
4 |
92 |
Europe |
92 |
|
Serbia |
44.01650 |
21.005900 |
2020-03-15 |
48 |
0 |
0 |
48 |
Europe |
48 |
|
Slovakia |
48.66900 |
19.699000 |
2020-03-15 |
54 |
0 |
0 |
54 |
Europe |
54 |
|
Slovenia |
46.15120 |
14.995500 |
2020-03-15 |
219 |
1 |
0 |
218 |
Europe |
218 |
|
Spain |
40.46367 |
-3.749220 |
2020-03-15 |
7798 |
289 |
517 |
6992 |
Europe |
6992 |
|
Sweden |
60.12816 |
18.643501 |
2020-03-15 |
1022 |
3 |
0 |
1019 |
Europe |
1019 |
|
Switzerland |
46.81820 |
8.227500 |
2020-03-15 |
2200 |
14 |
4 |
2182 |
Europe |
2182 |
| Channel Islands |
United Kingdom |
49.37230 |
-2.364400 |
2020-03-15 |
3 |
0 |
0 |
3 |
Europe |
3 |
| Isle of Man |
United Kingdom |
54.23610 |
-4.548100 |
2020-03-15 |
0 |
0 |
0 |
0 |
Europe |
0 |
|
United Kingdom |
55.37810 |
-3.436000 |
2020-03-15 |
3072 |
43 |
18 |
3011 |
Europe |
3011 |
|
Kosovo |
42.60264 |
20.902977 |
2020-03-15 |
0 |
0 |
0 |
0 |
Europe |
0 |
Ejercicio práctico: mi viaje a Potsman
Distancia euclídea:
\[d(x, y) = \sqrt{(x_{Lat} - y_{Lat})^2 +
(x_{Long} - y_{Long})^2}\]
distancia_grados <- function(x, y){
sqrt((x[1] - y[1])^2 + (x[2] - y[2])^2)
}
distancia_grados_potsdam <- function(x){
potsdam = c(52.366956, 13.906734)
distancia_grados(x, potsdam)
}
dist_potsdam <- apply(cbind(datos_europa$Latitud, datos_europa$Longitud),
MARGIN = 1,
FUN = distancia_grados_potsdam)
datos_europa %<>%
mutate(dist_potsdam = dist_potsdam)
datos_europa %>%
filter(between(Fecha, dmy("02-03-2020"), dmy("07-03-2020")),
dist_potsdam < 4) %>% # Radio menor de 4 grados
arrange(Pais_Region) %>% # Ordenar por país
kable()
|
Czechia |
49.81750 |
15.47300 |
2020-03-02 |
3 |
0 |
0 |
3 |
Europe |
3 |
2.992142 |
|
Czechia |
49.81750 |
15.47300 |
2020-03-03 |
5 |
0 |
0 |
5 |
Europe |
5 |
2.992142 |
|
Czechia |
49.81750 |
15.47300 |
2020-03-04 |
8 |
0 |
0 |
8 |
Europe |
8 |
2.992142 |
|
Czechia |
49.81750 |
15.47300 |
2020-03-05 |
12 |
0 |
0 |
12 |
Europe |
12 |
2.992142 |
|
Czechia |
49.81750 |
15.47300 |
2020-03-06 |
18 |
0 |
0 |
18 |
Europe |
18 |
2.992142 |
|
Czechia |
49.81750 |
15.47300 |
2020-03-07 |
19 |
0 |
0 |
19 |
Europe |
19 |
2.992142 |
|
Germany |
51.16569 |
10.45153 |
2020-03-02 |
159 |
0 |
16 |
143 |
Europe |
143 |
3.658073 |
|
Germany |
51.16569 |
10.45153 |
2020-03-03 |
196 |
0 |
16 |
180 |
Europe |
180 |
3.658073 |
|
Germany |
51.16569 |
10.45153 |
2020-03-04 |
262 |
0 |
16 |
246 |
Europe |
246 |
3.658073 |
|
Germany |
51.16569 |
10.45153 |
2020-03-05 |
482 |
0 |
16 |
466 |
Europe |
466 |
3.658073 |
|
Germany |
51.16569 |
10.45153 |
2020-03-06 |
670 |
0 |
17 |
653 |
Europe |
653 |
3.658073 |
|
Germany |
51.16569 |
10.45153 |
2020-03-07 |
799 |
0 |
18 |
781 |
Europe |
781 |
3.658073 |
Mapas del mundo con rnaturalearth
# Antes se necesita instalar rnaturalearthdata
#install.packages("rnaturalearthdata")
world <- ne_countries(scale = "medium", returnclass = "sf")
datos$Pais_Region = factor(datos$Pais_Region, levels = c(levels(datos$Pais_Region), "United States"))
datos[datos$Pais_Region == "US", ]$Pais_Region = "United States"
world %>%
inner_join(datos, by = c("name" = "Pais_Region")) %>%
filter(Fecha == dmy("30-05-2020")) %>%
ggplot() +
geom_sf(color = "black", aes(fill = Casos_Confirmados)) +
#coord_sf(crs = "+proj=laea +lat_0=50 +lon_0=10 +units=m +ellps=GRS80") +
scale_fill_viridis_c(option = "plasma", trans = "sqrt") +
xlab("Longitud") + ylab("Latitud") +
ggtitle("Mapa del mundo", subtitle = "COVID-19") -> g
ggplotly(g) # para hacer el mapa interativo